1. Field of the Invention
The present invention relates to reconstruction, a display and analysis of vascular tree structures and more specifically relates to reconstruction and of a moving cardiovascular tree structure from sequences of and geographic images and analysis of such a reconstructed moving model.
2. Discussion of Related Art
It is generally known in the art to display a reconstructed three-dimensional representation of a vascular tree structure from multiple two-dimensional radiographic images of the subject vascular tree structure. Co-pending patent application 09/444,138 teaches particular methods for accurately reconstructing a three-dimensional representation of a vascular tree structure from pairs of two-dimensional radiographic images each representing a view from a particular imaging angle. Such a three-dimensional reconstructed representation may be derived from, for example, a pair of images generated in a biplane radiographic imaging system or from a pair of images generated by a single plane radiographic imaging system positioned at each of two distinct viewing angles.
Such a three-dimensional reconstructed representation of a vascular tree structure is useful, as known in the art, for visualizing the vascular structure and for quantitative analysis of various measured attributes and parameters of selected portions of the vascular tree structure. For example, as discussed in co-pending patent application 09/444,138 such quantitative analysis and visualization is helpful for clinical procedures involving vascular implants and bypass procedures.
As presently practiced in the art, such visualization and quantitative analysis are applied only to a single, static frame of radiographic images—i.e., a snapshot in time. For example, biplane angiographs providing one static image of a coronary vascular structure in each of two viewing angles may be used to construct an accurate three-dimensional representation of the coronary vascular structure in one particular position corresponding to the static frame snapshot of the images. However, as commonly known in the art, vascular tree structures, especially coronary vascular structures, are in movement as blood is circulated through the structures.
In particular, coronary arteries and veins are dynamic, curvilinear structures that have a great degree of individual to individual variability and tortuosity. In the cardiovascular arena, percutaneous catheter-based interventional (i.e., therapeutic) procedures include a variety of coronary interventions, such as the placement of metal stents, atherectomy, radiation emitting catheters, devices to trap embolization of atherosclerotic debris, and placement of pacing electrodes in the coronary venous system. These procedures presently use two-dimensional X-ray based imaging as the sole or the major imaging modality for procedure guidance and quantification of key parameters. With the complex motions of the heart during each contraction, the degree of curvilinearity of coronary arteries undergoes a considerable change. Dynamic variations of coronary vascular curvilinearity have been very difficult to study because the forms of coronary angiographic imaging used clinically represent vascular structure only in two-dimensional format. Such a format does not provide anything but a rough semi-quantitative approach for studying the normal and changing curvilinearity of this coronary vascular tree and also limits the ability to quantify the degree of straightening caused by equipment transiently or permanently placed in coronary arteries during therapeutic procedures. Therefore, a quantitative description of coronary geometry and motion is required both for the mathematical modeling of arterial mechanics and for the evaluation and performance of a variety of current and emerging therapeutic procedures.
Some prior solutions have suggested coronary arterial movement analysis using bifurcation points or 3-D vessel centerlines of the coronary arterial tree. To facilitate the assessment of coronary arterial movements, it is necessary to recover the 3-D information of the coronary arterial tree throughout the cardiac cycle. These techniques provide limited analysis of a discrete set of points (the selected bifurcation points) of the arterial tree. Thorough analysis of the entire arterial tree, or arbitrary selected portions of the tree are not feasible when only discrete points are captured for analysis.
Other solutions suggest computer assisted techniques for estimation of the 3-D coronary arteries from biplane projection data have been reported. These methods were based on the known or standard X-ray geometry of projections, placement of landmarks, or the known vessel shape and on iterative identification of matching structures in two or more views. These reported techniques require a high degree of accuracy in the imaging equipment to record precise angles of imaging. Such accurate calibration is rare and generally not feasible in practical applications of such systems.
In another prior solution, a method based on motion and multiple views acquired in a single-plane imaging system was proposed. In these solutions, the motion transformations of the heart model consist only of rotation and scaling. By incorporation of the center-referenced method and initial depth coordinates and center coordinates, a 3-D skeleton of coronary arteries was obtained. This prior solution presumes a simplified model of the motion of the heart. In fact, cardiac movement is far more complex. Heart motion during contraction and relaxation actually involves five specific movements: translation, rotation, wringing, accordion-like motion, and movement toward to the center of chamber. The simplified model employed by this prior solution cannot therefore accurately model the true motion of the heart nor therefore of the cardiac arterial tree structure.
Other knowledge-based or rule-based systems have been proposed for 3-D reconstruction of coronary arteries by use of the model of a vascular network model. Because the rules or knowledge base were organized for certain specific conditions, it is not likely to generalize the 3-D reconstruction process to arbitrary projection data. These knowledge based systems utilize the knowledge of certain known heart conditions. These prior solutions do not therefore easily adapt to generalized aspects of cardiac motion nor to related arterial tree motion.
In yet another prior solution, the 3-D coronary arteries were reconstructed from a set of X-ray perspective projections by use of an algorithm from computed tomography. Due to the motion of heart, only a limited number of projections can be acquired. Therefore, accurate reconstruction and quantitative measurement are not easily achieved.
Closed-form solution of the 3-D reconstruction problem using a linear approach is suggested by still other prior solutions. Unfortunately, actual data are always corrupted by noise or errors and the linear approach based techniques may not be sufficiently accurate from noisy data.
In view of these various problems, optimal estimation has been explicitly investigated by still other prior solutions. A two-step approach has been proposed for an optimal estimation for a 3-D structure based on maximum-likelihood and minimum-variance estimation. Preliminary estimates computed by the linear algorithm were used as initial estimates for the process of optimal estimation. The second step to then refine the preliminary estimate can encounter mathematical problems if the preliminary estimate is too inaccurate as is often the case. In essence, the second refinement can get “trapped” in a sub-optimal mathematical solution by such an inaccurate preliminary estimate.
No presently practiced imaging techniques are known to provide for accurate reconstruction of a moving three-dimensional representation of a vascular tree structure. Neither is it presently known to provide for quantitative analysis of selected segments of such a reconstructed, moving three-dimensional representation of a vascular tree structure.
It is evident from the above discussion that a need exists for improved visualization and quantitative analysis techniques for reconstruction, display and analysis of a three-dimensional representation of a moving vascular tree structure. In particular, a need exists for improved techniques for visualizing and analyzing movements of a coronary vascular tree structure through a cardiac cycle from sequences of angiographic images.